Senior Data Engineer

Hours:

40 hours a week
Duration: 12 weeks, with expected extension into Phase 2
Start:
Immediately.

Location:

Remote, United States. Working hours overlap with U.S. Eastern time.

The role
Phase 1 involves little new pipeline building. The engineering job is to understand the data as it is: where it comes from, how it is mapped and transformed, which tables it lands in, and what the reports do with it. Both engineers need the same core skills so either can cover for the other. Each owns one track.

What engineer does
Profile source data from Salesforce, Net Suite, the payments platform and processor files.
Document source-to-target mappings and transformation logic.
Measure data quality: completeness, duplicates, and conflicting values across systems.
Help size the de-duplication work for the new unique customer key.
Write the reconciliation queries that test what the business analysts hear in interviews.
Contribute to the data inventory, the integration inventory and the KPI lineage.
Keep clear, reusable documentation. Phase 2 will be built from it.

Legacy Warehouse
The clients current data warehouse is SQL Server on AWS, built and run by an outside vendor. It is close to a black box: the vendor has not shared its business rules, transformation logic or lineage. This engineer takes it apart and documents it, so Proviniti can run it and the client can decide whether to keep it.
Inventory everything the warehouse runs: SSIS packages, stored procedures, SQL Server Agent jobs, schedules, alerts, credentials and manual fixes.
Extract the business rules from both places they live, the T-SQL in the warehouse and the DAX and Power Query behind about ten Power BI dashboards and the standard reports.
Build end-to-end lineage for each report, from source system to visual.
Shadow one monthly reporting cycle, which runs from the 18th to month-end, then run the next one.
Write the runbook Proviniti and the client will use after the vendor exits.
Recommend what to keep, what to rebuild, and what to retire.

Required
Expert T-SQL, including reading and refactoring stored procedures written by others.
SSIS and SQL Server Agent.
Power BI datasets, DAX and Power Query.
Reverse-engineering an undocumented warehouse or reporting system.
8 or more years in data engineering.
Expert SQL and strong data profiling.
Dimensional modeling, including slowly changing dimensions.
Clear written documentation of what you find.
Comfort working directly with client engineers and business users.

Preferred
SQL Server hosted on AWS EC2.
Migrating a SQL Server warehouse to Snowflake or another cloud platform.
Finance or month-end reporting.

What good looks like at week 12
Every warehouse job, rule, and report documented with lineage, one monthly cycle run by Proviniti, and a keep-or-replace recommendation.
Documentation the Phase 2 team can build from without going back to the vendor.